Differentiation of renal cell carcinoma subtypes by multislice computerized tomography

Dual-Energy Computed Tomography in Urological Diseases: A Narrative Review

Dual-Energy computed tomography (DECT) with its various advanced techniques, including Virtual Non-Contrast (VNC), effective atomic number (Z-eff) calculation, Z-maps, Iodine Density Index (IDI), and so on, holds great promise in the diagnosis and management of urogenital tumours. In this narrative review, we analyze the current status of knowledge of this technology to provide better lesion characterization, improve the staging accuracy, and give more precise treatment response assessments in relation to urological tumours.

The influence of manual segmentation strategies and different phases selection on machine learning-based computed tomography in renal tumors: a systematic review and meta-analysis

BACKGROUND

Delineating the region/volume of interest (ROI/VOI) and selecting the phases are of importance in developing machine learning (ML). The results will change when choosing different methods of drawing the ROI/VOI and selecting different phases. However, there is no related standard for delineating the ROI/VOI and selecting the phases in renal tumors to develop ML based on computed tomography (CT).

METHODS

The PubMed and Web of Science were searched for related studies published until March 1, 2023. Inclusion criteria were studies that developed ML models in renal tumors from CT images. And the binary diagnostic accuracy data were extracted to obtain the outcomes, such as sensitivity (SE), specificity (SP), accuracy (ACC), and area under the curve (AUC).

RESULTS

Twenty-three papers were included in the meta-analysis with a pooled SE of 87% (95% CI 85-88%), SP of 82% (95% CI 79-85%), and AUC of 91% (95% CI 89-93%) in phases; a pooled SE of 82% (95% CI 80-84%), SP of 85% (95% CI 83-86%), and AUC of 90% (95% CI 88-93%) in phases combined with delineating strategies, respectively. In all different combinations, the contour-focused and single phase produce the highest AUC of 93% (95% CI 90-95%). In subgroup analyses (sample size, year of publication, and geographical distribution), the performance was acceptable on phases and phases combined strategies.

CONCLUSIONS

To explore the effect of manual segmentation strategies and different phases selection on ML-based CT, we find that the method of single phase (CMP or NP) combined with contour-focused was considered a better strategy compared to the other strategies.

Artificial Intelligence-Based Non-invasive Differentiation of Distinct Histologic Subtypes of Renal Tumors With Multiphasic Multidetector Computed Tomography

INTRODUCTION

With rising cases of renal cell carcinoma (RCC), precise identification of tumor subtypes is essential, particularly for detecting small, heterogenous lesions often overlooked in traditional histopathological examinations. This study demonstrates the non-invasive use of deep learning for Histopathological differentiation of renal tumors through quadriphasic multidetector computed tomography (MDCT).

PATIENTS AND METHODS

This prospective longitudinal study includes 50 subjects (32 males, 18 females) with suspected renal tumors. A deep neural network (DNN) is developed to predict RCC subtypes using peak attenuation values measured in Hounsfield Units (HUs) obtained from quadriphasic MDCT scans. The network then generates confidence scores for each of the four primary subtypes of renal tumors, effectively distinguishing between benign oncocytoma and various malignant subtypes.

RESULTS

Our neural network accurately distinguishes Renal tumor subtypes, including clear cell, papillary, chromophobe, and benign oncocytoma, with a confidence score of 68% with the network's diagnosis aligning with Histopathological examinations. Our network was also able to accurately classify RCC subtypes on a synthetically generated dataset with 20,000 samples.

CONCLUSION

We developed an artificial intelligence-based RCC subtype classification technique. Our approach is non-invasive and has the potential to transform the methodology in Renal oncology by providing accurate and timely diagnostic information and enhancing clinical decisions.

Comparative study of conventional ROI-based and volumetric histogram analysis derived from CT enhancement in differentiating malignant and benign renal tumors

OBJECTIVE

To quantitatively compare the diagnostic values of conventional region of interest (ROI)-based and volumetric histogram analysis derived from CT enhancement in differentiating malignant and benign renal tumors.

METHODS

A total of 230 patients with pathologically confirmed renal tumors who had undergone CT enhancement were classified into clear cell renal cell carcinoma (ccRCC) (n = 133), non-ccRCC (n = 56), and benign renal tumor(n = 41) group. Parametric CT enhancement of each tumor from volumetric histogram were obtained using in-house software, including 10th percentile, 25th percentile, median, 75th percentile, 90th percentile, mean, standard deviation, as well as skewness, kurtosis and entropy, and histogram metrics among these groups were analyzed. ROI-based enhancement density was also analyzed.

RESULTS

The entropy and SD values of ccRCCs were higher than those of non-ccRCCs and benign renal tumors (p < 0.05). The 10th percentile, 25th percentile, median, 75th percentile, 90th percentile and mean values of ccRCCs were lower than those of benign renal tumors, however, higher than those of non-ccRCCs (p < 0.05). The ROI-based enhancement density of non-ccRCCs were lower than those of ccRCCs and benign renal tumors(p < 0.05). Receiver operating characteristic (ROC) curve analyses showed that entropy and mean values had the highest diagnostic efficacy in differentiating ccRCCs/non-ccRCCs and benign renal tumors. ROC curve analyses showed that mean values had the highest diagnostic efficacy in differentiating ccRCCs and non-ccRCCs. In terms of pairwise comparisons of ROC curves and diagnostic efficacy, ROI-based CT enhancement density was worse than volumetric histogram analysis (p < 0.05).

CONCLUSION

Volumetric histogram analysis parameters can effectively distinguish malignant and benign renal tumors.

ADVANCES IN KNOWLEDGE

1. Entropy and mean values had the highest diagnostic efficacy in differentiating ccRCCs/ non-ccRCCs and benign renal tumors.2. Mean values had the highest diagnostic efficacy in differentiating ccRCCs and non-ccRCCs.3.Volumetric histogram analysis had better performance than ROI-based enhancement density.

Value of energy spectrum CT parameters in the differential diagnosis of high-grade clear cell renal cell carcinoma and type II papillary renal cell carcinoma

BACKGROUND

Energy spectrum computed tomography (CT) has become a promising approach for the differential diagnosis of tumor subtypes.

PURPOSE

To explore the value of energy spectrum CT parameters in the differential diagnosis of high-grade clear cell renal cell carcinoma (ccRCC) and type II papillary renal cell carcinoma (pRCC).

MATERIAL AND METHODS

Forty-two cases of high-grade ccRCC and 28 cases of type II pRCC were retrospectively reviewed. All region of interest (ROI) measurements were maintained consistently between the two-phase contrast-enhanced examinations. The ROIs encompassed as much of the enhancing areas of the lesions as possible. Energy spectrum CT parameters of all cases, including the 70 keV (HU) value, normalized iodine concentration (NIC), and energy spectrum curve slope were recorded by two radiologists with over 10 years of experience in abdominal CT diagnosis.

RESULTS

In the cortical phase (CP) and parenchymal phase (PP), the 70 keV (HU) value, NIC, and slope value of the energy spectrum curve of high-grade ccRCC were significantly higher than those of type II pRCC. In the CP, NIC showed the highest differential diagnosis efficiency for the two group tumors, with a sensitivity of 78.9% and a specificity of 77.0%. There was no statistical difference in tumor hemorrhage, tumor envelope, tumor morphology, tumor border, lymph node metastasis, embolism, renal pelvis invasion, or tumor calcification between the two tumor types. However, there was significant difference in the number of tumors (P = 0.019).

CONCLUSION

Energy spectrum CT parameters are valuable for the differential diagnosis of high-grade ccRCC and type II pRCC.

Comparison of cortico-medullary phase contrast-enhanced MDCT and T2-weighted MR imaging in the histological subtype differentiation of renal cell carcinoma: radiology-pathology correlation

Purpose

Renal cell carcinoma (RCC) subtype differentiation is of crucial importance in the management and prognosis of these patients. In this study, we investigated the usefulness of unenhanced and cortico-medullary phase contrast-enhanced multidetector-row computed tomography (MDCT) and T2-weighted fast spin-echo (FSE) magnetic resonance imaging (MRI) modalities in the discrimination of the 3 main subtype RCC patients in correlation with their histopathological findings.

Material and methods

A total of 80 pathologically proven RCC patients who had undergone either partial or total nephrectomy were retrospectively investigated in this study. Their histological subtypes were 54 clear cell renal cell carcinoma (ccRCC), 15 papillary renal cell carcinoma (pRCC), and 11 chromophobe renal cell carcinoma (cRCC), based on pathological evaluation. There were 62 male (77.5%) and 18 female (22.5%) patients. Among the 54 ccRCC patients, 29 patients had both non-contrast and cortico-medullary phase CT, 1 had only non-contrast CT, 5 only had cortico-medullary phase CT, and 38 had MRI examination. In the pRCC group, 10 patients had both non-contrast and cortico-medullary phase CT, 1 had only non-contrast CT, 1 had only cortico-medullary phase CT, and 12 had MRI. Finally, in the remaining 11 cRCC patients, 9 had both non-contrast and cortico-medullary phase CT, and only 5 had MRI. We calculated both tumour attenuation values as HU (Hounsfield units) on unenhanced and cortico-medullary phase MDCT images and also tumour mean signal intensity values on FSE T2-weighted MRI images by using the region of interest (ROI) including normal renal cortex measurements. Besides quantitative evaluation, we also performed qualitative visual assessment of tumours on contrast-enhanced MDCT and FSE T2-weighted MRI.

Results

There was no statistically significant difference among the attenuation values of the 3 tumour subtypes on pre-contrast CT images. ccRCC demonstrated a prominent degree of contrast enhancement compared to the chromophobe and papillary ones on cortico-medullary phase MDCT. We found no statistically significant difference between chromophobe and papillary subtypes, although chromophobe tumours showed slightly higher attenuation values compared to papillary ones. ccRCCs usually demonstrated a heterogenous contrast enhancement on cortico-medullary phase CT images, while the papillary subtype usually had a homogenous appearance on visual assessment. On FSE T2-weighted MR images, the signal intensity values of ccRCC patients were found to be significantly higher than both chromophobe and papillary subtypes. Although cRCC patients had a prominently lower T2 signal intensity than clear cell subtype, there was no statistically significant signal intensity difference between chromophobe and papillary subtypes. Regarding visual assessment, papillary subtype tumours showed a mostly homogenous appearance on T2-weighted images and a statistically significant difference was present. On the other hand, there was no significant difference of visual assessment of the clear cell and chromophobe subtypes.

Conclusions

The measurement of the attenuation values on cortico-medullary phase MDCT and the mean signal intensity values on FSE T2-weighted MRI can provide useful information in the differentiation of RCC main subtypes. Also, visual assessment of tumours on both modalities can contribute to this issue by providing additional imaging properties.

CT and MRI findings of cystic renal cell carcinoma: comparison with cystic collecting duct carcinoma

BACKGROUND

Cystic renal cell carcinoma (CRCC) and cystic collecting duct carcinoma (CCDC) share similar oncogeni and some imaging findings. The aim of this study was to characterize the clinical and CT imagings features of CRCC and CCDC.

METHODS

Thirty-three patients with CRCC and thirteen patients with CCDC with pathologically proven were retrospectively studied. Tumor characteristics were assessed.

RESULTS

On CT imaging, 33 patients(100 %) with CRCC and 13 patients(100 %) with CCDC, tumors calcifications (8 vs. 9, P < 0.0001), had a clear boundary (capsule sign, 30 vs. 2, P < 0.0001), infiltrative appearance (1 vs. 13, P < 0.0001), exogenous appearance (29 vs. 3, P < 0.0001), invaded the renal pelvis or ureter (1 vs. 10, P < 0.0001), hemorrhage (1 vs. 10, P < 0.0001), had retroperitoneal lymph node or distant metastasis (2 vs. 10, P < 0.0001), thickened enhancing internal septations (31 vs. 2, P < 0.0001), and mural soft-tissue nodules (21 vs. 1, P < 0.0001). On MR imaging,13 patients(39 %) with CRCC and 4 patients(31 %) with CCDC, all CRCCs appeared hypointense on T1-weighted images and hyperintense on T2-weighted images, however, all CCDCs appeared hypointense on T1-weighted images and hypointense on T2-weighted images(P < 0.0001). 33 patients with CRCC, they were all alive from3 years to 10 years follow-up, however, 13 patients with CCDC, of which 11 patients were able to be followed up, and 9 patients expired within 5 years of the initial diagnosis and the others are currently still alive.

CONCLUSIONS

Distinguishing features of CRCC and CCDC included calcifications, capsule signs, infiltrative appearance, metastasis, internal septations, mural nodules and signal on CT or MR images. These imaging features may help in differentiating the two renal tumor types.

The role of imaging in the management of renal masses

The wide availability of cross-sectional imaging is responsible for the increased detection of small, usually asymptomatic renal masses. More than 50 % of renal cell carcinomas (RCCs) represent incidental findings on noninvasive imaging. Multimodality imaging, including conventional US, contrast-enhanced US (CEUS), CT and multiparametric MRI (mpMRI) is pivotal in diagnosing and characterizing a renal mass, but also provides information regarding its prognosis, therapeutic management, and follow-up. In this review, imaging data for renal masses that urologists need for accurate treatment planning will be discussed. The role of US, CEUS, CT and mpMRI in the detection and characterization of renal masses, RCC staging and follow-up of surgically treated or untreated localized RCC will be presented. The role of percutaneous image-guided ablation in the management of RCC will be also reviewed.

Correlation between CT and anatomopathological staging of kidney cancer

Our Moroccan context is experiencing an increase in the frequency of renal tumors. This trend can be explained by the generalization of the use of imaging, in particular abdominal ultrasound, which has become almost systematic among general practitioners (Godley and Ataga, 2000 [1]). The specificity of kidney cancer is anatomopathological heterogenicity: histological type, nuclear grade, tumor stage, these elements constitute the most important prognostic factors. Renal biopsy appears to be a safe and reliable solution with a low risk of tumor seeding and complications, however it cannot provide all the detailed histological information needed. Hence the interest in the abdominal scanner. The abdominal scanner is the reference examination for the evaluation of renal tumors, it diagnoses the tumor, specifies these characteristics, it assesses the loco regional, venous extension. The objective of our study is to correlate pathological and CT findings of 70 kidney cancer in order to determine the reliability of CT in kidney cancer and its extension.

Using texture analysis as a predictive factor of subtype, grade and stage of renal cell carcinoma

OBJECTIVE

The aim of this study was to evaluate the correlation between the tissue texture analysis and the histological subtypes, grade and stage of the disease in patients with renal cell carcinoma (RCC).

MATERIALS AND METHODS

Seventy-seven patients who underwent computed tomography due to renal mass and diagnosed with RCC as a result of pathological examination were retrospectively analyzed. In these analyses, the demographic characteristics, pathological and radiological findings of the patients were evaluated. The masses were introduced to the Radiomics extension of the software and the first- and second-order texture analysis parameters were obtained. The correlation of these parameters with histological subtype, Fuhrman grade and TNM stage was investigated.

RESULTS

In the comparison of the Radiomics values by stages, "minimum", "Long Run Low Gray-level Emphasis" values were higher in the stage 1-2 group, while "Energy", "Total energy", "Range", "Joint Average", "Sum Average", "Gray-Level Non-Uniformity", "Short-Run High Gray-level Emphasis ", "Run Length Non-Uniformity "and "High Gray-Level Run Emphasis "values were higher in the stage 3-4 group. Of these parameters, only "Gray-Level Non-Uniformity" and "Run Length Non-Uniformity'' values were significantly lower in tumors with low Fuhrman grade (1-2) and low TNM stage (1-2). There was no statistically significant correlation between the parameters found to be significant in histological subtype differentiation and Fuhrman grade and TNM stage.

CONCLUSION

This study demonstrates that "Gray-Level Non-Uniformity" and "Run Length Non-Uniformity "parameters in the texture analysis method can be used to evaluate the prognosis in patients with RCC.

Differential diagnosis of chromophobe renal cell carcinoma and papillary renal cell carcinoma with dual-energy spectral computed tomography

BACKGROUND

Computed tomography (CT) image features of chromophobe renal cell carcinoma (ChRCC) and papillary renal cell carcinoma (PRCC) are, occasionally, sometimes difficult to identify. However, spectral CT might provide quantitative parameters to differentiate them.

PURPOSE

To differentiate between ChRCC and PRCC with quantitative parameters using spectral CT.

MATERIAL AND METHODS

Forty cases of RCC confirmed with pathological tests were analyzed retrospectively (27 cases of PRCC and 13 cases of ChRCC). All patients underwent non-enhanced CT and dual-phase contrast-enhanced CT scans. For each lesion, the CT value of monochromatic images as well as iodine and water concentrations were measured, and the slope of spectrum curve was calculated. Data were analyzed using Student's t-test. Sensitivity and specificity of the quantitative parameters were analyzed using the receiver operating characteristic (ROC) curve.

RESULTS

During the cortex phase (CP) and parenchyma phase (PP), the CT value and slope of spectrum curve of ChRCC were higher than those of PRCC, and significant differences were observed at low energy levels (40-70 keV). Normalized iodine concentration of ChRCC and that of PRCC was significantly different during CP and PP (P < 0.05). The water (iodine) concentrations of ChRCC and PRCC in CP and PP were not statistically different (P > 0.05). All the ROCs for parameters were above the reference line.

CONCLUSION

Spectral CT may help increase the diagnostic accuracy of differentiating PRCC from ChRCC using a quantitative analysis.

Differentiation of Clear Cell Renal Cell Carcinoma from other Renal Cell Carcinoma Subtypes and Benign Oncocytoma Using Quantitative MDCT Enhancement Parameters

Background and objectives: The use of non-invasive techniques to predict the histological type of renal masses can avoid a renal mass biopsy, thus being of great clinical interest. The aim of our study was to assess if quantitative multiphasic multidetector computed tomography (MDCT) enhancement patterns of renal masses (malignant and benign) may be useful to enable lesion differentiation by their enhancement characteristics. Materials and Methods: A total of 154 renal tumors were retrospectively analyzed with a four-phase MDCT protocol. We studied attenuation values using the values within the most avidly enhancing portion of the tumor (2D analysis) and within the whole tumor volume (3D analysis). A region of interest (ROI) was also placed in the adjacent uninvolved renal cortex to calculate the relative tumor enhancement ratio. Results: Significant differences were noted in enhancement and de-enhancement (diminution of attenuation measurements between the postcontrast phases) values by histology. The highest areas under the receiver operating characteristic curves (AUCs) of 0.976 (95% CI: 0.924–0.995) and 0.827 (95% CI: 0.752–0.887), respectively, were demonstrated between clear cell renal cell carcinoma (ccRCC) and papillary RCC (pRCC)/oncocytoma. The 3D analysis allowed the differentiation of ccRCC from chromophobe RCC (chrRCC) with a AUC of 0.643 (95% CI: 0.555–0.724). Wash-out values proved useful only for discrimination between ccRCC and oncocytoma (43.34 vs 64.10, p < 0.001). However, the relative tumor enhancement ratio (corticomedullary (CM) and nephrographic phases) proved useful for discrimination between ccRCC, pRCC, and chrRCC, with the values from the CM phase having higher AUCs of 0.973 (95% CI: 0.929–0.993) and 0.799 (95% CI: 0.721–0.864), respectively. Conclusions: Our observations point out that imaging features may contribute to providing prognostic information helpful in the management strategy of renal masses.

Effect of phase of enhancement on texture analysis in renal masses evaluated with non-contrast-enhanced, corticomedullary, and nephrographic phase-enhanced CT images

OBJECTIVE

To compare texture analysis (TA) features of solid renal masses on renal protocol (non-contrast enhanced [NECT], corticomedullary [CM], nephrographic [NG]) CT.

MATERIALS AND METHODS

A total of 177 consecutive solid renal masses (116 renal cell carcinoma [RCC]; 51 clear cell [cc], 40 papillary, 25 chromophobe, and 61 benign masses; 49 oncocytomas, 12 fat-poor angiomyolipomas) with three-phase CT between 2012 and 2017 were studied. Two blinded radiologists independently assessed tumor heterogeneity (5-point Likert scale) and segmented tumors. TA features (N = 25) were compared between groups and between phases. Accuracy (area under the curve [AUC]) for RCC versus benign and cc-RCC versus other masses was compared.

RESULTS

Subjectively, tumor heterogeneity differed between phases (p < 0.01) and between tumors within the same phase (p = 0.03 [NECT] and p < 0.01 [CM, NG]). Inter-observer agreement was moderate to substantial (intraclass correlation coefficient = 0.55-0.73). TA differed in 92.0% (23/25) features between phases (p < 0.05) except for GLNU and f6. More TA features differed significantly on CM (80.0% [20/25]) compared with NG (40.0% [10/25]) and NECT (16.0% [4/25]) (p < 0.01). For RCC versus benign, AUCs of texture features did not differ comparing CM and NG (p > 0.05), but were higher for 20% (5/25) and 28% (7/25) of features comparing CM and NG with NECT (p < 0.05). For cc-RCC versus other, 36% (9/25) and 40% (10/25) features on CM had higher AUCs compared with NECT and NG images (p < 0.05).

CONCLUSION

Texture analysis of renal masses differs, when evaluated subjectively and quantitatively, by phase of CT enhancement. The corticomedullary phase had the highest discriminatory value when comparing masses and for differentiating cc-RCC from other masses.

KEY POINTS

• Subjectively evaluated renal tumor heterogeneity on CT differs by phase of enhancement. • Quantitative CT texture analysis features in renal tumors differ by phases of enhancement with the corticomedullary phase showing the highest number and most significant differences compared with non-contrast-enhanced and nephrographic phase images. • For diagnosis of clear cell RCC, corticomedullary phase texture analysis features had improved accuracy of classification in approximately 40% of features studied compared with non-contrast-enhanced and nephrographic phase images.

Small renal masses (≤ 4 cm): differentiation of oncocytoma from renal clear cell carcinoma using ratio of lesion to cortex attenuation and aorta-lesion attenuation difference (ALAD) on contrast-enhanced CT

PURPOSE

We investigate the use of ratio of lesion to cortex (L/C) attenuation and aorta-lesion attenuation difference (ALAD) on multiphase contrast-enhanced CT to help distinguish oncocytoma from clear cell RCC in small renal masses (diameter < 4 cm).

METHODS

We retrospectively identified 76 patients that undergo CT before surgery for a suspicious small renal mass between January 2014 and December 2018 with pathological diagnosis of 21 oncocytomas (ROs), 25 clear cell RCCs, 7 chromophobe RCCs, 7 papillary RCCs, 7 multilocular cystic RCCs, 7 angiomyolipomas and 2 leiomyomas. CT attenuation values were obtained for the tumor, the normal renal cortex and the aorta, placing a circular region of interest (ROI) in the same slice by two radiologists, independently.

RESULTS

In the corticomedullary phase, ROs showed isodense enhancement to the renal cortex (ratio L/C 0.92 ± 0.12), while clear cell RCCs appeared hypodense to the renal cortex (ratio L/C 0.69 ± 0.20; p < 0.01) with an accuracy of 80% for diagnosing RO. In nephrographic phase, the ratio L/C attenuation was lower than the corticomedullary phase in ROs (0.78 ± 0.11) showing an early washout pattern, while the ratio L/C was similar to the corticomedullary phase in clear cell RCCs (0.69 ± 0.13; p = 0.025, with an accuracy of 65% for diagnosing RO). The ratio L/C attenuation showed considerable overlap between ROs and clear cell RCCs in the excretory phase (p = 0.27). Mean ALAD values in the nephrographic phase were 21.95 ± 16.24 for ROs and 36.96 ± 30.53 for clear cell RCCs (p = 0.049).

CONCLUSION

The ratio L/C attenuation in corticomedullary phase may be useful to differentiate RO from clear cell RCC.

Differentiation of renal cell carcinoma subtypes through MRI-based radiomics analysis

OBJECTIVES

To explore whether clear cell renal cell carcinoma (ccRCC), papillary renal cell carcinoma (pRCC), and chromophobe renal cell carcinoma (cRCC) can be distinguished using radiomics features extracted from magnetic resonance (MR) images.

METHODS

Seventy-seven patients (ccRCC = 32, pRCC = 23, cRCC = 22) underwent MRI before surgery between May 2013 and August 2018 in this retrospective study. Thirty-nine radiomics features were extracted from tumor volumes on three sequences (T2WI, EN-T1WI CMP, and EN-T1WI NP). The Kruskal-Wallis test with Bonferonni correction and variance threshold were used for feature selection among the three RCC subtypes. ROC curves for the three subtypes were generated based on radiomics features. AUC, accuracy, sensitivity, and specificity for subtype differentiation are reported. Linear discriminant analysis (LDA) was used to assess the discriminative ability of these radiomics features.

RESULTS

Significant radiomics features among the three subtypes were identified, and ROC curves achieved excellent AUCs for T2WI, EN-T1WI CMP, EN-T1WI NP, and combined three MR sequences (0.631, 0.790, 0.959, and 0.959 between ccRCC and cRCC; 0.688, 0.854, 0.909, and 0.955 between pRCC and cRCC; 0.747, 0.810, 0.814, and 0.890 between ccRCC and pRCC). In addition, LDA demonstrated the three RCC subtypes were correctly classified by radiomics analysis (66.2% for EN-T1WI CMP, 71.4% for EN-T1WI NP, 55.8% for T2WI, and 71.4% for the combined three MR sequences).

CONCLUSIONS

Radiomics analysis can be used to differentiate among ccRCC, pRCC, and cRCC based on radiomics features extracted from multiple-sequence MRI and may help diagnose and treat RCC patients in the future, while further study is still needed.

KEY POINTS

• Radiomics features on multiple-sequence MRI can help differentiate the three subtypes of renal cell carcinoma (clear cell, papillary renal cell, and chromophobe renal cell carcinoma). • Radiomics features based on MRI indicate greater textural heterogeneity on ccRCCs than pRCCs and cRCCs (the highest AUCs on EN-T1WI NP are 0.814 for ccRCCs vs pRCCs and 0.959 for ccRCCs vs cRCCs, respectively). • There is a significant difference in the textural heterogeneity of radiomics features between pRCCs and cRCCs (the AUC is 0.909, 0.854, and 0.688 on EN-T1WI NP, EN-T1WI CMP, and T2WI, respectively).

[Concordances and predictors of biopsies in renal tumors]

AIM

Evaluate the concordance between the renal lesions biopsy's histology and the final histology of the surgical specimen according to histological subtype, and search for predictive factors of non-concordance.

MATERIAL

We performed a monocentric retrospective study that included 156 patients suffering from a renal tumor that benefited a lesion biopsy before surgical treatment. Sensibility and specificity of the renal lesion's biopsy for histological diagnostic of the different renal tumors where calculated.

RESULTS

One hundred and fifty-eight renal tumor biopsies were realized between 2001 and 2016. One hundred and forty-three renal cell carcinoma were found on the surgical piece, 135 were diagnosed on prior biopsy. Global concordance rate was 88%. For the establishment of the nuclear Fuhrmann grade, the concordance rate (low vs. high grade) was 72.9%. The cohort was divided into 2 groups according to the existence (group 1, n=139) or the absence (group 2, n=19) of concordance. Group 1 and 2 differed by the predominance of men in group 1 (66% vs. 37%, P=0.013), distance between the sinus and the tumor above 4mm (65% vs. 42%, P=0.05).

CONCLUSION

In renal tumor care, renal biopsy is a reliable testing. However, some factors most likely linked to the tumor anatomy (intra-sinusal tumor) and their histological composition were involved in the lack of non-contribution to the diagnosis.

LEVEL OF EVIDENCE

4.

Pan-Renal Cell Carcinoma classification and survival prediction from histopathology images using deep learning

Histopathological images contain morphological markers of disease progression that have diagnostic and predictive values. In this study, we demonstrate how deep learning framework can be used for an automatic classification of Renal Cell Carcinoma (RCC) subtypes, and for identification of features that predict survival outcome from digital histopathological images. Convolutional neural networks (CNN's) trained on whole-slide images distinguish clear cell and chromophobe RCC from normal tissue with a classification accuracy of 93.39% and 87.34%, respectively. Further, a CNN trained to distinguish clear cell, chromophobe and papillary RCC achieves a classification accuracy of 94.07%. Here, we introduced a novel support vector machine-based method that helped to break the multi-class classification task into multiple binary classification tasks which not only improved the performance of the model but also helped to deal with data imbalance. Finally, we extracted the morphological features from high probability tumor regions identified by the CNN to predict patient survival outcome of most common clear cell RCC. The generated risk index based on both tumor shape and nuclei features are significantly associated with patient survival outcome. These results highlight that deep learning can play a role in both cancer diagnosis and prognosis.

CT texture analysis in the differentiation of major renal cell carcinoma subtypes and correlation with Fuhrman grade

OBJECTIVE

CT texture analysis (CTTA) using filtration-histogram-based parameters has been associated with tumor biologic correlates such as glucose metabolism, hypoxia, and tumor angiogenesis. We investigated the utility of these parameters for differentiation of clear cell from papillary renal cancers and prediction of Fuhrman grade.

METHODS

A retrospective study was performed by applying CTTA to pretreatment contrast-enhanced CT scans in 290 patients with 298 histopathologically confirmed renal cell cancers of clear cell and papillary types. The largest cross section of the tumor on portal venous phase axial CT was chosen to draw a region of interest. CTTA comprised of an initial filtration step to extract features of different sizes (fine, medium, coarse spatial scales) followed by texture quantification using histogram analysis.

RESULTS

A significant increase in entropy with fine and medium spatial filters was demonstrated in clear cell RCC (p = 0.047 and 0.033, respectively). Area under the ROC curve of entropy at fine and medium spatial filters was 0.804 and 0.841, respectively. An increased entropy value at coarse filter correlated with high Fuhrman grade tumors (p = 0.01). The other texture parameters were not found to be useful.

CONCLUSION

Entropy, which is a quantitative measure of heterogeneity, is increased in clear cell renal cancers. High entropy is also associated with high-grade renal cancers. This parameter may be considered as a supplementary marker when determining aggressiveness of therapy.

KEY POINTS

• CT texture analysis is easy to perform on contrast-enhanced CT. • CT texture analysis may help to separate different types of renal cancers. • CT texture analysis may enhance individualized treatment of renal cancers.

Current Management of Small Renal Masses, Including Patient Selection, Renal Tumor Biopsy, Active Surveillance, and Thermal Ablation

Renal cancer represents 2% to 3% of all cancers, and its incidence is rising. The increased use of ultrasonography and cross-sectional imaging has resulted in the clinical dilemma of incidentally detected small renal masses (SRMs). SRMs represent a heterogeneous group of tumors that span the full spectrum of metastatic potential, including benign, indolent, and more aggressive tumors. Currently, no composite model or biomarker exists that accurately predicts the diagnosis of kidney cancer before treatment selection, and the use of renal mass biopsy remains controversial. The management of SRMs has changed dramatically over the last two decades as our understanding of tumor biology and competing risks of mortality in this population has improved. In this review, we critically assess published consensus guidelines and recent literature on the diagnosis and management of SRMs, with a focus on patient treatment selection and use of renal mass biopsy, active surveillance, and thermal ablation. Finally, we highlight important opportunities for leveraging recent research discoveries to identify patients with SRMs at high risk for renal cell carcinoma-related mortality and minimize overtreatment and patient morbidity.

Clear cell renal cell carcinoma: identifying PTEN expression on multiphasic MDCT

PURPOSE

To investigate whether multiphasic MDCT enhancement profiles can help to identify PTEN expression in clear cell renal cell carcinomas (ccRCCs). Lack of PTEN expression is associated with worsened overall survival, a more advanced Fuhrman grade, and a greater likelihood of lymph mode metastasis.

METHODS

With IRB approval for this retrospective study, we derived a cohort of 103 histologically proven ccRCCs with preoperative 4-phase renal mass MDCT from 2001-2013. Following manual segmentation, a computer-assisted detection algorithm selected a 0.5-cm-diameter region of maximal attenuation within each lesion in each phase; a 0.5-cm-diameter region of interest was manually placed on uninvolved renal cortex in each phase. The relative attenuation of each lesion was calculated as [(Maximal lesion attenuation - cortex attenuation)/cortex attenuation] × 100. Absolute and relative attenuation in each phase were compared using t tests. The performance of multiphasic enhancement in identifying PTEN expression was assessed with logistic regression analysis.

RESULTS

PTEN-positive and PTEN-negative ccRCCs both exhibited peak enhancement in the corticomedullary phase. Relative corticomedullary phase attenuation was significantly greater for PTEN-negative ccRCCs in comparison to PTEN-positive ccRCCs (33.7 vs. 9.5, p = 0.03). After controlling for lesion stage and size, relative corticomedullary phase attenuation had an accuracy of 84% (86/103), specificity of 100% (84/84), sensitivity of 11% (2/19), positive predictive value of 100% (2/2), and negative predictive value of 83% (84/101) in identifying PTEN expression.

CONCLUSION

Relative corticomedullary phase attenuation may help to identify PTEN expression in ccRCCs, if validated prospectively.

Utility of multiphasic multidetector computed tomography in discriminating between clear cell renal cell carcinomas with high and low carbonic anhydrase-IX expression

PURPOSE

To investigate if multiphasic multidetector computed tomography (MDCT) enhancement profiles can distinguish clear cell renal cell carcinomas (ccRCCs) with high carbonic anhydrase-IX (CA-IX) expression from ccRCCs with low CA-IX expression.

METHODS

With IRB approval for this retrospective study, we derived a cohort of 105 histologically proven ccRCCs with preoperative 4-phase renal mass MDCT from 2001 to 2013. Following manual segmentation, the computer-assisted detection algorithm selected a 0.5-cm-diameter region of maximal attenuation within each lesion in each phase. CA-IX expression level was determined by immunohistochemical staining of tumor specimens. In the high and low CA-IX expression subgroups, the magnitude of enhancement and washout were compared using t tests; the performance of contrast washout in differentiating between subgroups was assessed with logistic regression analysis.

RESULTS

ccRCCs with high and low CA-IX expression both exhibited peak enhancement in the corticomedullary phase. ccRCCs with high CA-IX expression demonstrated significantly greater relative nephrographic washout than those with low CA-IX expression (18.4% vs. 7.8%, p = 0.03). ccRCCs with high CA-IX expression had greater relative excretory washout than ccRCCs with low CA-IX expression with a trend toward significance (33.4% vs. 25.2%, p = 0.05). After controlling for tumor size and stage, for distinguishing ccRCCs with high and low CA-IX expression, relative excretory washout had a sensitivity, negative predictive value, accuracy, and positive predictive value of 99% (65/66), 88% (7/8), 69% (72/105), and 67% (65/97), respectively.

CONCLUSION

Relative nephrographic and excretory washout may have the potential to help distinguish ccRCCs with high and low CA-IX expression, but this requires further validation.

Intrarenal urothelial cancers confused as infiltrative renal masses: Report of 22 cases and literature review

Distinguishing infiltrative renal masses (IRMs) from intrarenal urothelial cancers (IUCs) is critically important, but may be challenging for any radiologist or urologist. The present study aimed to summarize the clinical, imaging and pathological characteristics of IRM, which were postoperatively confirmed as IUC. The analysis was performed using the records of 22 patients who were preoperatively diagnosed with IRM but the results of percutaneous biopsies or postoperative pathological analyses led to diagnoses of urothelial cancers (UCs) from January 2011 to December 2017. The demographic data, computed tomography (CT) imaging features and pathological characteristics were evaluated. The present study also reviewed the literature concerning the IRM and IUC. The mean age of patients was 62 years and 86.4% of them were >55 years. The sex and tumor side distributions were equal. Hematuria and/or flank pain were observed in 86.4% of patients. All patients exhibited endophytic solid renal masses with unclear tumor boundaries on CT images. The kidneys of 81.8% of patients maintained their normal shape while mild alternations were observed in 18.2% of cases. A total of 81.8% of patients maintained the reniform shape and 18.2% exhibited mild contour change. Of all patients, all tumors exhibited less or equal attenuation on unenhanced CT images and they were mildlyimproved on enhanced CT. A total of 6 cases were confirmed by biopsy, when patients underwent laparoscopic nephroureterectomy instead of radical nephrectomy. The remaining 16 patients underwent laparoscopic nephrectomy but the postoperative pathological diagnoses revealed the presence of UCs. All postoperatively confirmed cancers were stages T3 and T4 (62.5 and 37.5%, respectively). UCs should be suspected in middle aged or elderly middle-elderly patients presenting renal masses with endophytic solid unclear tumor boundary on unenhanced and slightly enhanced CT images, accompanied with hematuria and/or flank pain. Preoperative biopsy is preferred for complicated cases.

Imaging of Solid Renal Masses

The increase in serendipitous detection of solid renal masses on imaging has not resulted in a reduction in mortality from renal cell carcinoma. Consequently, efforts for improved lesion characterization have been pursued and incorporated into management algorithms for distinguishing clinically significant tumors from those with favorable histology or benign conditions. Although diagnostic imaging strategies have evolved for optimized lesion detection, distinction between benign tumors and both indolent and aggressive malignant neoplasms remain an important diagnostic challenge. Recent advances in cross-sectional imaging have expanded the role of these tests in the noninvasive characterization of solid renal tumors.

Fat poor angiomyolipoma differentiation from renal cell carcinoma at 320-slice dynamic volume CT perfusion

PURPOSE

To compare various CT perfusion features of fat poor angiomyolipoma (AML) with those of size-matched renal cell carcinoma (RCC).

METHODS

One hundred and seventy-four patients [16 with fat poor AML (mean diameter, 3.1 cm; range, 1.5-5.5 cm) and 158 with RCC (mean diameter, 3.2 cm; range, 2.4-5.4 cm)] who had undergone 320-slice dynamic volume CT perfusion were evaluated. Equivalent blood volume (BV _Equiv), permeability surface-area product (PS), and blood flow (BF) of tumor were measured and analyzed. Fat poor AML was compared with each subtype of RCC (132 clear cell, 9 papillary, and 17 chromophobe). Receiver operating characteristic (ROC) curve analysis was performed for the comparison of fat poor AML and RCC. ROC curve analysis was not performed for the papillary RCC subtype because of the small number of masses of this subtype.

RESULTS

BV _Equiv and BF were significantly lower in fat poor AML than in clear cell RCC (P < 0.05 for both). Fat poor AML had higher BV _Equiv, PS, and BF than papillary RCC (P < 0.05 for all). PS and BF in fat poor AML significantly exceeded those in chromophobe RCC (P < 0.05 for both). For differentiating fat poor AML from clear cell RCC, area under the ROC curve (AUC) of BV _Equiv and BF were 0.82 and 0.69. Using the optimal threshold value, the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were 0.82, 0.81, 0.35, 0.97 for BV _Equiv and 0.71, 0.75, 0.24, 0.96 for BF, respectively. For differentiating fat poor AML from chromophobe RCC, AUC of PS and BF were 0.77 and 0.79, respectively. The optimal sensitivity, specificity, PPV, and NPV were 0.77, 0.75, 0.75, 0.76 for PS and 0.71, 0.81, 0.72, 0.80 for BF, respectively.

CONCLUSIONS

Fat poor AML and subtypes of RCCs demonstrate different perfusion features at 320-slice dynamic volume CT, allowing their differentiations with BV _Equiv, PS, and BF being valuable perfusion parameters.

Diagnostic Accuracy of Unenhanced CT Analysis to Differentiate Low-Grade From High-Grade Chromophobe Renal Cell Carcinoma

OBJECTIVE

The objective of our study was to evaluate tumor attenuation and texture on unenhanced CT for potential differentiation of low-grade from high-grade chromophobe renal cell carcinoma (RCC).

MATERIALS AND METHODS

A retrospective study of 37 consecutive patients with chromophobe RCC (high-grade, n = 13; low-grade, n = 24) who underwent preoperative unenhanced CT between 2011 and 2016 was performed. Two radiologists (readers 1 and 2) blinded to the histologic grade of the tumor and outcome of the patients subjectively evaluated tumor homogeneity (3-point scale: completely homogeneous, mildly heterogeneous, or mostly heterogeneous). A third radiologist, also blinded to tumor grade and patient outcome, measured attenuation and contoured tumors for quantitative texture analysis. Comparisons were performed between high-grade and low-grade tumors using the chi-square test for subjective variables and sex, independent t tests for patient age and tumor attenuation, and Mann-Whitney U tests for texture analysis. Logistic regression models and ROC curves were computed.

RESULTS

There were no differences in age or sex between the groups (p = 0.652 and 0.076). High-grade tumors were larger (mean ± SD, 62.6 ± 34.9 mm [range, 17.0-141.0 mm] vs 39.0 ± 17.9 mm [16.0-72.3 mm]; p = 0.009) and had higher attenuation (mean ± SD, 45.5 ± 8.2 HU [range, 29.0-55.0 HU] vs 35.3 ± 8.5 HU [14.0-51.0 HU]; p = 0.001) than low-grade tumors. CT size and attenuation achieved good accuracy to diagnose high-grade chromophobe RCC: The AUC ± standard error was 0.85 ± 0.08 (p < 0.0001) with a sensitivity of 69.0% and a specificity of 100%. Subjectively, high-grade tumors were more heterogeneous (mildly or markedly heterogeneous: 69.2% [9/13] for reader 1 and 76.9% [10/13] for reader 2; reader 1, p = 0.024; reader 2, p = 0.001) with moderate agreement (κ = 0.57). Combined texture features diagnosed high-grade tumors with a maximal AUC of 0.84 ± 0.06 (p < 0.0001).

CONCLUSION

Tumor attenuation and heterogeneity assessed on unenhanced CT are associated with high-grade chromophobe RCC and correlate well with the histopathologic chromophobe tumor grading system.

Pathological heterogeneity in sporadic synchronous renal tumors: Is the histological concordance predictable?

OBJECTIVE

To evaluate the pathological concordance rate of multiple synchronous renal masses (MSRM) presumed to be sporadic and to analyze predictive factors of concordance.

MATERIAL AND METHODS

We identified from our institutional database patients with sporadic MSRM treated at our center between January 2000 and December 2015. All tumors were reviewed by a dedicated uropathologist. Pathological concordance rate was analyzed regarding clinical characteristics and preoperative imaging.

RESULTS

We included 112 patients: 50 had unilateral synchronous renal masses and 62 bilateral synchronous renal masses. A total of 291 tumors were analyzed, with an average of 2.6 tumors per patient. Overall, the malignant concordance rate was 91.6%, the pathological concordance rate was 67.3% and the grade concordance rate was 62.5%. In univariate analysis, predictive factors of histological concordance were bilateral synchronous renal masses (odds ratio [OR] = 3.39; 95% CI: 1.06-10.8; P = 0.04), age<60 years (OR = 3.04; 95% CI: 1.2-7.7; P = 0.02) and ≥3 lesions (OR = 2.41; 95% CI: 1.03-5.68; P = 0.04). In multivariate analysis, age<60 remained significantly associated with histological concordance (OR = 3.84; 95% CI: 1.24-11.9; P = 0.02).

CONCLUSIONS

The histological concordance rate of MSRM is low. Age at diagnosis <60 years, bilateral lesions and ≥3 tumors are predictive factors of histological concordance, but the pathological diagnosis remains difficult to predict. This heterogeneity is important to take into account, particularly when choosing the treatment upon the renal biopsy results from a single lesion.

Sarcomatoid Renal Cell Carcinoma and Collecting Duct Carcinoma: Discrimination From Common Renal Cell Carcinoma Subtypes and Benign RCC Mimics on Multiphasic MDCT

RATIONALE AND OBJECTIVES

To investigate whether imaging features on multiphasic multidetector computed tomography (MDCT) can help discriminate sarcomatoid renal cell carcinoma (RCC) and collecting duct carcinoma (CDC) from other solid renal masses.

MATERIALS AND METHODS

With institutional review board approval for this HIPAA-compliant study, we derived a cohort of 7 sarcomatoid RCCs, 4 CDCs, 165 clear cell RCCs, 56 papillary RCCs, 22 chromophobe RCCs, 49 oncocytomas, and 16 lipid-poor angiomyolipomas with preoperative multiphasic MDCT with up to four phases (unenhanced, corticomedullary, nephrographic, and excretory). Each lesion was reviewed for contour, spread pattern, pattern of enhancement, neovascularity, and calcification.

RESULTS

Sarcomatoid RCCs and CDCs were more likely than other solid renal masses to have an irregular contour (64% vs 2%, P < 0.001) and an infiltrative spread pattern, defined as infiltration into adjacent renal parenchyma, collecting system, or neighboring structures (82% vs 7%, P < 0.001). When used to discriminate sarcomatoid RCC and CDC from other solid renal masses, an infiltrative spread pattern had a specificity of 93% (287/308) and sensitivity of 82% (9/11), and an irregular contour had a specificity of 98% (303/308) and sensitivity of 64% (7/11).

CONCLUSIONS

Solid renal lesions with an irregular contour or an infiltrative spread pattern are suspicious for sarcomatoid RCC or CDC.

Role of Contrast Enhancement and Corrected Attenuation Values of Renal Tumors in Predicting Renal Cell Carcinoma (RCC) Subtypes: Protocol for a Triphasic Multi-Slice Computed Tomography (CT) Procedure

BACKGROUND

To distinguish RCC subtypes based on contrast enhancement features of CT images.

MATERIAL/METHODS

In total, 59 lesions from 57 patients were included. All patients underwent multi-slice CT imaging with a triphasic protocol, which included non-contrast, corticomedullary, nephrographic and urographic phases. Contrast enhancement features of renal masses were evaluated in terms of CT attenuation values (AV) and differences in contrast density; the aorta or renal parenchyma were evaluated based on corrected or relative values.

RESULTS

Clear cell RCC (ccRCC) showed more intense contrast enhancement than other RCC subtypes. When differentiating ccRCC from other RCC subtypes, a cut-off AV of 86-89 HU, aorta-based corrected AV of 89-95 HU and renal parenchyma-based corrected AV of 87-95 HU showed a diagnostic accuracy of 81-86%, 86-88% and 74-78%, respectively, in the corticomedullary phase. Furthermore, a cutoff of 2.42-2.72 for the relative contrast enhancement ratio, a cutoff of 2.59-2.74 for the aorta-based corrected relative contrast enhancement ratio and a cutoff of 2.63-2.76 for the renal parenchyma-based attenuation ratio showed a diagnostic accuracy of 83-88%, 88-90% and 81%, respectively.

CONCLUSIONS

The most reliable parameters for differentiating ccRCC from other RCC subtypes are aorta-based corrected AV and aorta-based corrected relative contrast enhancement values in the corticomedullary phase.

Type 1 papillary renal cell carcinoma: differentiation from Type 2 papillary RCC on multiphasic MDCT

PURPOSE

To investigate whether multiphasic MDCT enhancement can help differentiate type 1 papillary renal cell carcinoma (RCC) from type 2 papillary RCC.

METHODS

With IRB approval for this HIPAA-compliant retrospective study, we derived a cohort of 36 type 1 papillary RCCs and 33 type 2 papillary RCCs with preoperative multiphasic MDCT with up to four phases (unenhanced, corticomedullary, nephrographic, and excretory) from 2000 to 2013. Following segmentation, a computer-assisted detection (CAD) algorithm selected a 0.5 cm-diameter region of maximal attenuation within each lesion in each phase; a 0.5 cm-diameter region of interest was manually placed on uninvolved renal cortex in each phase. The relative attenuation of each lesion was calculated as [(Lesion attenuation-cortex attenuation)/cortex attenuation] × 100. Absolute and relative attenuation values were compared using Mann-Whitney tests with Bonferroni correction for multiple comparisons.

RESULTS

Relative excretory phase attenuation of type 2 papillary RCCs was significantly greater than that of type 1 papillary RCCs (2.0 vs. -18.3, p = 0.005). Relative excretory phase attenuation differentiated type 1 papillary RCCs from type 2 papillary RCCs with an accuracy of 73% (36/49), sensitivity of 87% (26/30), positive predictive value of 74% (26/35), and negative predictive value of 71% (10/14).

CONCLUSION

Multiphasic MDCT enhancement may assist in differentiating type 1 papillary RCCs from type 2 papillary RCCs, if prospectively validated.

Clear Cell Renal Cell Carcinoma: Identifying the Loss of the Y Chromosome on Multiphasic MDCT

OBJECTIVE

The objective of our study was to investigate whether multiphasic MDCT enhancement can help identify clear cell renal cell carcinomas (RCCs) with the loss of the Y chromosome.

MATERIALS AND METHODS

We derived a cohort of 43 clear cell RCCs in men who underwent preoperative four-phase renal mass MDCT from October 2000 to August 2013. Each lesion was segmented in its entirety on axial images. A computer-assisted detection algorithm selected a 0.5-cm-diameter region of maximal attenuation within each lesion in each phase. A 0.5-cm-diameter ROI was manually placed on uninvolved renal cortex in each phase. The relative attenuation of each lesion was calculated as follows: [(maximal lesion attenuation - cortex attenuation) / cortex attenuation] × 100. Absolute attenuation and relative attenuation in each phase were compared using t tests.

RESULTS

Both clear cell RCCs with the loss of the Y chromosome and clear cell RCCs without the loss of the Y chromosome exhibited peak enhancement in the corticomedullary phase. However, relative nephrographic attenuation of clear cell RCCs with the loss of Y was significantly less than that of clear cell RCCs without the loss of Y (mean, -8.9 vs 8.4 respectively; p = 0.013). A relative nephrographic attenuation threshold of -1.6 identified the loss of Y with an accuracy of 70% (30/43), sensitivity of 73% (16/22), and specificity of 67% (14/21).

CONCLUSION

Multiphasic MDCT enhancement may assist in identifying the loss of the Y chromosome in clear cell RCCs; this result should be validated in a large prospective trial.

Preoperative Lymphocyte-Monocyte Ratio Ameliorates the Accuracy of Differential Diagnosis in Non-Metastatic Infiltrative Renal Masses

PURPOSE

Distinguishing infiltrative renal cell carcinoma (RCC) from transitional cell carcinoma (TCC) is a challenging issue due to their radiologic similarities. We evaluated systemic inflammatory biomarkers as parameters for distinguishing tumor types.

MATERIALS AND METHODS

A computerized search of medical records from November 2005 to October 2015 identified 116 patients with infiltrative renal masses who were difficult to diagnose confirmatively in radiological study. We investigated the diagnostic efficacy among these patients with their preoperative absolute neutrophil counts (ANC), absolute lymphocyte counts (ALC), absolute monocyte counts (AMC), neutrophil-lymphocyte ratio (NLR), and lymphocyte-monocyte ratio (LMR).

RESULTS

The infiltrative RCC group demonstrated significantly lower ALC {1449/μL (1140-1896), median [interquartile range (IQR)]} than the TCC group [1860/μL (1433-2342), p=0.016]. LMR [median (IQR)] also was lower in the infiltrative RCC group [2.98 (2.32-4.14) vs. TCC group 4.10 (2.86-6.09); p=0.011]. In subgroup analysis, non-metastatic infiltrative RCC showed lower ALC and LMR and higher NLR than non-metastatic TCC. Within non-metastatic infiltrative renal masses, multivariate logistic regression analysis revealed that younger patient age and lower LMR were associated with infiltrative RCC [odds ratios (OR) 0.874, p=0.024 and OR 0.461, p=0.048, respectively]. Receiver operating characteristic curve analysis showed that younger age and lower LMR were highly predictive of non-metastatic RCC (area under the curve=0.919, p<0.001).

CONCLUSION

Age and LMR were significantly different between patients with infiltrative renal mass. These are potential markers for distinguishing between infiltrative RCC and TCC without metastasis.

Imaging of Solid Renal Masses

Detection of solid renal masses has increased, although it has not resulted in significant mortality reduction from renal cell carcinoma. Efforts for improved lesion characterization have been pursued and incorporated in management algorithms, in order to distinguish clinically significant tumors from favorable or benign conditions. Concurrently, imaging methods have produced evidence supporting their role as useful tools not only in lesion detection but also characterization. In addition, newer modalities, such as contrast-enhanced ultrasonography, and advanced applications of MR imaging, are being investigated. This article reviews the current role of different imaging methods in the characterization of solid renal masses.

Differentiation of subtypes of renal cell carcinoma with contrast-enhanced ultrasonography

We aimed to assess the difference of enhancement patterns among the three RCC subtypes with contrast-enhanced ultrasound (CEUS). Two hundreds cases of pathologically proved clear cell renal cell carcinomas (ccRCC), 58 papillary renal cell carcinomas (pRCC) and 51 chromophobe renal cell carcinomas (chRCC) underwent preoperative conventional ultrasound and CEUS. The wash-in and wash-out pattern, peak enhancement degree and homogeneity, and the presence of pseudocapsule were evaluated by two blinded observers respectively. The interreader agreement in the characterization of CEUS features between two observers was good (κ  = 0.649-0.775). Compared with pRCCs and chRCCs, ccRCCs demonstrated higher frequency of simultaneous wash-in pattern, hyperenhancement and heterogeneity with necrotic areas. Most pRCCs and chRCCs manifested hypoenhancement, homogeneity, fast wash-out and presence of pseudocapsule. The only difference we obtained between pRCC and chRCC was the wash-in pattern, with slow wash-in in pRCC and simultaneous wash-in in chRCC. In small lesions with long diameter≤3 cm, the majority of the three subtypes of RCC showed homogeneous enhancement and there was no difference among them. CEUS was a useful method to preoperatively differentiate the ccRCC from non-ccRCC subtypes. There were no distinguishing features identifid on CEUS that allowed reliable differentiation of pRCC from chRCC.

Clear cell renal cell carcinoma: identifying the gain of chromosome 12 on multiphasic MDCT

PURPOSE

To determine whether multiphasic MDCT enhancement can help identify the gain of chromosome 12 in clear cell renal cell carcinomas (RCCs).

METHODS

With IRB approval for this HIPAA-compliant case control study, we derived a cohort of 65 clear cell RCCs with preoperative four-phase renal mass MDCT from October 2000 to August 2013. Each lesion was segmented in its entirety on axial images in all phases. A computer-assisted detection (CAD) algorithm selected a 0.5-cm-diameter region of maximal attenuation within each lesion in each phase. Attenuation in each phase between clear cell RCCs with and without the gain of 12 was compared using t-tests.

RESULTS

While the entire cohort of clear cell RCCs exhibited peak enhancement in the corticomedullary phase, the subcohort of lesions with the gain of 12 exhibited significantly greater enhancement in the nephrographic (179 vs. 145 HU, p = 0.004) and excretory phases (147 vs. 118 HU, p = 0.004) than the subcohort of lesions without the gain of 12. A nephrographic threshold of 186 HU identified the gain of 12 with an accuracy of 86% (56/65), specificity of 93% (51/55), and negative predictive value of 91% (51/56).

CONCLUSION

Multiphasic MDCT enhancement, specifically enhancement in the nephrographic and excretory phases, may potentially assist in identifying the gain of 12 in clear cell RCCs.

Multimodality Imaging Characteristics of the Common Renal Cell Carcinoma Subtypes: An Analysis of 544 Pathologically Proven Tumors

Objectives:

The objective of this study was to define the characteristic imaging appearances of the common renal cell carcinoma (RCC) subtypes.

Materials and Methods:

The Institutional Review Board approval was obtained for this HIPAA-compliant retrospective study, and informed consent was waived. 520 patients (336 men, 184 women; age range, 22–88 years) underwent preoperative cross-sectional imaging of 544 RCCs from 2008 to 2013. The imaging appearances of the RCCs and clinical information were reviewed. Data analysis was performed using parametric and nonparametric statistics, descriptive statistics, and receiver operating characteristic analysis.

Results:

The RCC subtypes showed significant differences (P < 0.001) in several imaging parameters such as tumor margins, tumor consistency, tumor homogeneity, the presence of a central stellate scar, T2 signal intensity, and the degree of tumor enhancement. Low T2 signal intensity on magnetic resonance imaging (MRI) allowed differentiation of papillary RCC from clear cell and chromophobe RCCs with 90.9% sensitivity and 93.1% specificity. A tumor-to-cortex ratio ≥1 on the corticomedullary phase had 98% specificity for clear cell RCC.

Conclusion:

The T2 signal intensity of the tumor on MRI and its degree of enhancement are useful imaging parameters for discriminating between the RCC subtypes while gross morphological findings offer additional value in RCC profiling.

Correlating Preoperative Imaging with Histologic Subtypes of Renal Cell Carcinoma and Common Mimickers

Renal cell carcinoma (RCC) consists of distinct subtypes that have unique pathologic and imaging features as well as specific cytogenetic and molecular characteristics. As the prognosis and therapeutic strategies may differ for each subtype, correlation of the preoperative imaging with the pathologic findings is of great clinical relevance. In addition, differentiation of RCC from benign entities is ideal in order to prevent overtreatment. However, a noninvasive diagnosis with imaging alone is not always straightforward due to the overlapping appearance of RCC with benign lesions such as fat-poor angiomyolipoma and oncocytoma. With new imaging modalities, there have been significant improvements in correlating preoperative imaging with pathologic characteristics. These new discoveries are able to aid in a more specific, noninvasive, diagnosis that in turn helps direct patient management.

Renal cell carcinoma: applicability of the apparent coefficient of the diffusion-weighted estimated by MRI for improving their differential diagnosis, histologic subtyping, and differentiation grade

BACKGROUND

Renal cell carcinoma (RCC) represents the most common malignant epithelial neoplasm of the kidney. Accurate assessment of the renal masses, defining the histologic subtype and the grade of differentiation of the tumor, is vital to ensure an adequate case management as well as for staging and prognosis. Recently, diffusion-weighted imaging (DWI) magnetic resonance imaging (MRI) tends to be increasingly appealing for the clinicians as an imaging procedure of choice for the diagnosis and staging of the RCC, which is predetermined by several advantages over CT. The goal of the survey was to assess the applicability of the apparent diffusion coefficient (ADC) of the DWI MRI for the differential diagnostics, histologic subtyping, and defining the grade of differentiation of the RCC.

METHODS

The study enrolled 288 adult patients with renal lesions: 188 patients with solid RCC-126 patients with clear cell subtype (ccRCC), 32 patients with papillary RCC (pRCC), 30 patients with chromophobe RCC (chRCC); 27 patient with cystic form or RCC (Bosniak cyst, category IV); 32 patients with renal angiomyolipoma (AML); 25 patients with renal oncocytoma (OC); and 16 patients with the renal abscess (AB). In total, 245 lesions were pathologically verified. As a reference, 19 healthy volunteers were included into the study. All patients underwent MRI of the kidneys, involving DWI with subsequent evaluation of the ADC.

RESULTS

There was a reliable difference (p < 0.05) in mean ADC values between the normal renal parenchyma (NRP), solid RCC of different histologic subtypes and grades, cystic RCC, and benign renal lesions. The mean ADC values obtained in the result of the study were (×10^-3 mm²/s): 2.47 ± 0.12 in NRP, 1.63 ± 0.29 in all solid RCCs, 1.82 ± 0.22 in solid ccRCC (1.92 ± 0.11-Fuhrman grade I, 1.84 ± 0.14-Fuhrman grade II, 1.79 ± 0.10-Fuhrman grade III, 1.72 ± 0.06-Fuhrman grade IV), 1.61 ± 0.07 in pRCC, 1.46 ± 0.09 in chRCC, 2.68 ± 0.11 in cystic RCC, 2.13 ± 0.08 in AML, 2.26 ± 0.06 in OC, and 3.30 ± 0.07 in AB.

CONCLUSION

The data received in our study demonstrate a substantial restriction of diffusion of hydrogen molecules in tissues of ccRCC in comparison with the healthy renal parenchyma preconditioned by the greater density of tumor. A statistically significant difference in mean ADC values of ccRCC with different grades of nuclear pleomorphism by Fuhrman was observed: Low-grade tumors showed higher mean ADC values compared to high-grade tumors. The modality of the MRI DWI along with ADC measurement allows to reliably differentiate between the solid RCC of main histologic subtypes and grades, cystic RCC, and the benign renal lesions.

Clear cell renal cell carcinoma: identifying the gain of chromosome 20 on multiphasic MDCT

PURPOSE

To investigate whether multiphasic multidetector computed tomography (MDCT) enhancement can help identify the gain of chromosome 20 in clear cell renal cell carcinomas (RCCs), a rare prognostically significant cytogenetic abnormality.

METHODS

With the Institutional Review Board approval, we queried our institution's pathology database to derive a cohort of 52 cases of clear cell RCC with preoperative four-phase renal mass protocol MDCT and karyotypes of the resected specimens during a 10-year period. Each lesion was evaluated for absolute and relative (compared to contralateral normal renal cortex) attenuations in each phase. Relative attenuation was calculated as [(lesion attenuation - cortex attenuation)/cortex attenuation] × 100. The absolute and relative attenuations were compared using t-tests.

RESULTS

Clear cell RCCs with the gain of 20 had significantly less nephrographic and excretory phase enhancement than clear cell RCCs without the gain of 20 (86.4 HU vs. 111.4 HU, p = 0.007; 70.0 HU vs. 89.4 HU, p = 0.003; respectively). Additionally, the relative nephrographic and excretory phase attenuations of clear cell RCCs with the gain of 20 were significantly less than that of clear cell RCCs without the gain of 20 (-52.7 vs. -34.7, p = 0.002; -44.9 vs. -31.1, p = 0.005; respectively).

CONCLUSION

Multiphasic MDCT enhancement may assist in identifying the gain of chromosome 20 in clear cell RCCs, if validated in a large prospective trial.

Diagnostic accuracy of contrast-enhanced computed tomography and contrast-enhanced magnetic resonance imaging of small renal masses in real practice: sensitivity and specificity according to subjective radiologic interpretation

Background

The aim of this study was to investigate the diagnostic accuracy of contrast-enhanced computed tomography (CT) and contrast-enhanced magnetic resonance imaging (MRI) of small renal masses in real practice.

Methods

Contrast-enhanced CT and MRI were performed between February 2008 and February 2013 on 68 patients who had suspected small (≤4 cm) renal cell carcinoma (RCC) based on ultrasonographic measurements. CT and MRI radiographs were reviewed, and the findings of small renal masses were re-categorized into five dichotomized scales by the same two radiologists who had interpreted the original images. Receiver operating characteristics curve analysis was performed, and sensitivity and specificity were determined.

Results

Among the 68 patients, 60 (88.2 %) had RCC and eight had benign disease. The diagnostic accuracy rates of contrast-enhanced CT and MRI were 79.41 and 88.23 %, respectively. Diagnostic accuracy was greater when using contrast-enhanced MRI because too many masses (67.6 %) were characterized as “4 (probably solid cancer) or 5 (definitely solid cancer).” The sensitivity of contrast-enhanced CT and MRI for predicting RCC were 79.7 and 88.1 %, respectively. The specificities of contrast-enhanced CT and MRI for predicting RCC were 44.4 and 33.3 %, respectively. Fourteen diagnoses (20.5 %) were missed or inconsistent compared with the final pathological diagnoses. One appropriate nephroureterectomy and five unnecessary percutaneous biopsies were performed for RCC. Seven unnecessary partial nephrectomies were performed for benign disease.

Conclusions

Although contrast-enhanced CT and MRI showed high sensitivity for detecting small renal masses, specificity remained low.

Differentiation of subtypes of renal cell carcinoma: dynamic contrast-enhanced magnetic resonance imaging versus diffusion-weighted magnetic resonance imaging

OBJECTIVE

The objective was to compare the performance of dynamic contrast-enhanced (DCE) and diffusion-weighted (DW) magnetic resonance (MR) imaging in the differentiation of subtypes of renal cell carcinoma (RCC).

MATERIALS/METHODS

This study included 45 renal tumors of clear cell (n=36) and non-clear-cell (n=9) RCC. The contrast enhancement ratios (CERs) and the apparent diffusion coefficient (ADC) values on MR imaging were compared between the clear cell and non-clear-cell RCC groups.

RESULTS

In the comparison of diagnostic performance between DCE and DW MR imaging, areas under the curves were 0.968 and 0.797 for the CERs of the corticomedullary and the ADC value.

CONCLUSION

The CER of the corticomedullary phase was more reliable in distinguishing between clear cell and non-clear-cell RCCs.

Angiomyolipoma with minimal fat: differentiation of morphological and enhancement features from renal cell carcinoma at CT imaging

BACKGROUND

Angiomyolipoma (AML) with minimal fat may mimic renal cell carcinoma (RCC) and is difficult to distinguish from RCC with imaging studies alone. Precise diagnostic strategies have been explored to discern AML with minimal fat from RCC.

PURPOSE

To compare the morphological and enhancement features of AML with minimal fat with those of size-matched RCC on computed tomography (CT).

MATERIAL AND METHODS

Our study included 143 pathologically proved renal tumors (29 AML with minimal fat: mean diameter, 2.5 cm; range, 1.2-4 cm; 114 RCC: mean diameter, 2.8 cm; range, 1.3-4 cm). All patients underwent biphasic helical CTs. Two radiologists retrospectively evaluated the morphological (i.e. non-round and round appearances, with or without capsule) and enhancement features (i.e., wash-out, gradual, or prolonged). For the parameters that had statistically significance between the two groups, we calculated the positive and negative predictive values by using the univariate χ(2) test. P < 0.05 indicated a significant difference.

RESULTS

AML with minimal fat showed a non-round appearance without a capsule (n = 24, 83%) and prolonged enhancement (n = 20, 69%). The positive and negative predictive values of the non-round appearance without capsule for differentiating AML with minimal fat from RCC were 82.8% and 95.6%, respectively. The positive and negative predictive values of prolonged enhancement were 62.5% and 90.8%, respectively. These features were valuable predictors for AML with minimal fat from RCC.

CONCLUSION

CT images with non-round shape without capsule and prolonged enhancements may be used to differentiate AML with minimal fat from RCC.

Quantitative assessment of solid renal masses by contrast-enhanced ultrasound with time-intensity curves: how we do it

PURPOSE

To discuss the evaluation of the enhancement curve over time of the major renal cell carcinoma (RCC) subtypes, oncocytoma, and lipid-poor angiomyolipoma, to aid in the preoperative differentiation of these entities. Differentiation of these lesions is important, given the different prognoses of the subtypes, as well as the desire to avoid resecting benign lesions.

METHODS

We discuss findings from CT, MR, and US, but with a special emphasis on contrast-enhanced ultrasound (CEUS). CEUS technique is described, as well as time-intensity curve analysis.

RESULTS

Examples of each of the major RCC subtypes (clear cell, papillary, and chromophobe) are shown, as well as examples of oncocytoma and lipid-poor angiomyolipoma. For each lesion, the time-intensity curve of enhancement on CEUS is reviewed, and correlated with the enhancement curve over time reported for multiphase CT and MR.

CONCLUSIONS

Preoperative differentiation of the most common solid renal masses is important, and the time-intensity curves of these lesions show some distinguishing features that can aid in this differentiation. The use of CEUS is increasing, and as a modality it is especially well suited to the evaluation of the time-intensity curve.

Usefulness of MDCT to Differentiate Between Renal Cell Carcinoma and Oncocytoma: Development of a Predictive Model

OBJECTIVE

The objective of our study was to identify the most useful parameters to differentiate between renal cell carcinoma (RCC) and oncocytoma using four-phase CT.

MATERIALS AND METHODS

Ninety-seven patients with solid renal lesions who underwent surgery with four-phase preoperative CT evaluation and with pathologic diagnosis of RCC or oncocytoma were included in the study. Features of tumors and the enhancement pattern in the four CT phases were evaluated and analyzed. Logistic regression models were used to assess independent predictors for malignancy.

RESULTS

Histopathologically, 13 tumors were oncocytomas and 84 were RCCs. RCCs were larger (6.20 cm vs 3.21 cm, p = 0.0004) and more often enhanced heterogeneously (66 vs 6, p = 0.02). Lesions that were larger than 4 cm showed a significantly higher risk of malignancy (p = 0.0046). Significant differences were found in intensity of nodule enhancement between the nephrographic and the excretory phases with respect to the unenhanced phase (p = 0.003 and p = 0.0026). At multivariate analysis, parameters that were independent predictors of malignancy were enhancement pattern, with RCCs more often having heterogeneous enhancement than oncocytomas (odds ratio [OR], 0.18; 95% CI, 0.04-0.90), and nodule enhancement in the excretory phase in relation to the unenhanced phase, with RCCs showing lower enhancement (OR, 0.93; 95% CI, 0.88-0.97), and a size larger than 4 cm (OR, 4.01; 95% CI, 0.70-23.14).

CONCLUSION

The combination of different CT parameters including lesion size larger than 4 cm, lesion enhancement in the excretory phase in relation to the unenhanced phase, and heterogeneous enhancement pattern helps distinguish RCC from oncocytoma.

Likelihood of Incomplete Kidney Tumor Ablation with Radio Frequency Energy: Degree of Enhancement Matters

PURPOSE

Larger size and clear cell histopathology are associated with worse outcomes for malignant renal tumors treated with radio frequency ablation. We hypothesize that greater tumor enhancement may be a risk factor for radio frequency ablation failure due to increased vascularity.

MATERIALS AND METHODS

A retrospective review of patients who underwent radio frequency ablation for renal tumors with contrast enhanced imaging available was performed. The change in Hounsfield units (HU) of the tumor from the noncontrast phase to the contrast enhanced arterial phase was calculated. Radio frequency ablation failure rates for biopsy confirmed malignant tumors were compared using the chi-squared test. Multivariate logistic analysis was performed to assess predictive variables for radio frequency ablation failure. Disease-free survival was calculated using Kaplan-Meier analysis.

RESULTS

A total of 99 patients with biopsy confirmed malignant renal tumors and contrast enhanced imaging were identified. The incomplete ablation rate was significantly lower for tumors with enhancement less than 60 vs 60 HU or greater (0.0% vs 14.6%, p=0.005). On multivariate logistic regression analysis tumor enhancement 60 HU or greater (OR 1.14, p=0.008) remained a significant predictor of incomplete initial ablation. The 5-year disease-free survival for size less than 3 cm was 100% vs 69.2% for size 3 cm or greater (p <0.01), while 5-year disease-free survival for HU change less than 60 was 100% vs 92.4% for HU change 60 or greater (p=0.24).

CONCLUSIONS

Biopsy confirmed malignant renal tumors, which exhibit a change in enhancement of 60 HU or greater, experience a higher rate of incomplete initial tumor ablation than tumors with enhancement less than 60 HU. Size 3 cm or greater portends worse 5-year disease-free survival after radio frequency ablation. The degree of enhancement should be considered when counseling patients before radio frequency ablation.